Search

Despite their role in host nutrition, the anaerobic gut fungal (AGF) component of the herbivorous gut microbiome remains poorly characterized. Here, to examine global patterns and determinants of AGF diversity, we generate and analyze an amplicon dataset from 661 fecal samples from 34 mammalian species, 9 families, and 6 continents. We identify 56 novel genera, greatly expanding AGF diversity beyond current estimates (31 genera and candidate genera). Community structure analysis indicates that host phylogenetic affiliation, not domestication status and biogeography, shapes the community rather than. Fungal-host associations are stronger and more specific in hindgut fermenters than in foregut fermenters. Transcriptomics-enabled phylogenomic and molecular clock analyses of 52 strains from 14 genera indicate that most genera with preferences for hindgut hosts evolved earlier (44-58 Mya) than those with preferences for foregut hosts (22-32 Mya). Our results greatly expand the documented scope of AGF diversity and provide an ecologically and evolutionary-grounded model to explain the observed patterns of AGF diversity in extant animal hosts.

A general computational model covering many types of frictional contact interfaces between visco-elastic bodies is considered for some cases physically relevant in numerical analysis of contact in civil engineering structures. The relations between mechanical quantities and internal parameters of the model are illustrated in a couple of simplified examples including cohesive contact combined with Coulomb friction and/or interface plasticity. The computations are implemented a semi-implicit time discretisation, quadratic programming algorithms, and the boundary-element method.

A quasi-static model for numerical solution of initiation and propagation of cracks along interfaces or inside materials is developed. The two types of cracks are modelled by the material damage theory with two independent damage parameters introduced. For cracks at the interface, in fact represented by contact of construction components, cohesive or adhesive contact is considered, for which several computational relationships based on energetic formulation exist. Accordingly, the appropriate modelling of bulk damage also includes energy consideration. In terms of cracks, it leads to so called diffuse cracks. The computational approach is referred to as phase field models. These will cause damage in a very narrow band representing the actual crack. The computational analysis provides stress-strain quantities and the damage variables to simulate both interface and material cracks. The proposed mathematical approach has a variational form based on an energetic formulation looking for a kind of weak solution. The solution is approximated by a time stepping procedure, a finite element code, and it utilizes quadratic programming algorithms.

A mathematical model of a layered structure and initiation and growth of interface cracks are presented. A numerical approach for solving this problem is described, with the emphasis to the analysis of a shearing-mode crack. The model defines a scalar damage variable in the interface and also plastic tangential slip, which increases the fracture toughness in the shearing crack mode. An energetic formulation governing the adhesive damage until it breaks is proposed. The approach is also tested numerically to demonstrate the behaviour of the model and to assess its suitability in a particular physical situation.

Reconstructing the evolution of brain information-processing capacity is paramount for understanding the rise of complex cognition. Comparative studies of brain evolution typically use brain size as a proxy. However, to get a less biased picture of the evolutionary paths leading to high cognitive power, we need to compare brains not by mass but by numbers of neurons, which are their basic computational units. This study reconstructs the evolution of brains across amniotes by directly analyzing neuron numbers by using the largest dataset of its kind and including essential data on reptiles. We show that reptiles have not only small brains relative to body size but also low neuronal densities, resulting in average neuron numbers over 20 times lower than those in birds and mammals of similar body size. Amniote brain evolution is characterized by the following four major shifts in neuron-brain scaling. The most dramatic increases in brain neurons occurred independently with the appearance of birds and mammals, resulting in convergent neuron scaling in the two endotherm lineages. The other two major increases in the number of neurons happened in core land birds and anthropoid primates, which are two groups known for their cognitive prowess. Interestingly, relative brain size is associated with relative neuronal cell density in reptiles, birds, and primates but not in other mammals. This has important implications for studies using relative brain size as a proxy when looking for evolutionary drivers of animal cognition. [ABSTRACT FROM AUTHOR]